diskussionspapier nr. 15 des instituts für ... · allroggen / malina: market power of hub airports...

Diskussionspapier Nr. 15

des Instituts für Verkehrswissenschaft

MARKET POWER OF HUB AIRPORTS:

THE ROLE OF LOCK-IN EFFECTS AND

DOWNSTREAM COMPETITION

Florian Allroggen

Robert Malina

Am Stadtgraben 9

48143 Münster

Juli 2010

Allroggen / Malina: Market Power of Hub Airports

Diskussionspapier Nr. 15 des Instituts für Verkehrswissenschaft

1

MARKET POWER OF HUB AIRPORTS: THE ROLE OF LOCK-IN EFFECTS AND

DOWNSTREAM COMPETITION

Florian Allroggen,

Institute of Transport Economics,

University of Muenster/Germany

E-mail: [email protected]

Robert Malina

Institute of Transport Economics,

University of Muenster/Germany

E-mail: [email protected]

ABSTRACT

In this paper we develop a model of hub competition, which includes duopolistic Bertrand

competition on the downstream market in order to analyze the incentives of hub airports to

exploit market power in the transfer passenger market. We find evidence that downstream

competition limits hub market power and moreover, that there are incentives for a hub airport

and its respective network carrier to optimize profits of the overall network jointly. Therefore,

strict economic regulation of the business relationship between hub airports and their

respective network carrier is rendered unnecessary. Regulators should focus on supporting

long-term profit sharing contracts of network carriers and hub airports or other contractual

forms to ensure vertical cooperation.

Keywords: Airports, Regulation, Hub Competition

1 INTRODUCTION

The market-power of a hub airline at a hub airport has widely been discussed theoretically

and empirically.1 Much less emphasis has been laid upon the question, as to whether a hub

airport has market power and is able to exploit the market power in its business relationship

to the hub airline. The same notion is true for the regulatory consequences that arise from

the nature of the relationship between hub airport and hub airline.

Hub airports are often considered to be monopolists in the business relationship with the

respective network carrier.2 This finding is a consequence of the lock-in effect that is

assumed to arise for the network carrier at the airport. This lock-in effect might result from

idiosyncratic investments in flight schedules or maintenance facilities. As these investments

are sunk costs with high quasi-rents, they can be exploited by the airport by charging high

1 See e.g. Borenstein (1989) Kahn (1993), Lijesen et al. (2000) or van Dender (2007).

2 See e.g. Beckers et al. (2010) who only see a low level of network competition for German Airports.



2

prices for aviation services and/or offering poor service quality without having to fear that the

airline shifts its hub operations to another airport.

However, employing such a strategy might not be profit maximizing, as it lowers the demand

for the hub airline as passenger shift to other network airlines using other hubs and offering

lower prices or better services, which, in turn, leads to lower demand for services of the hub

airport that exploits market power. Competition in the downstream airline market drives the

need for efficient and high quality services in the upstream market and, therefore, limits the

incentives of hub airports to exploit market power.

In this paper we will give some insight into the incentives of a hub airport for using its market

power from a game theoretical industrial economics perspective. In section 2 we analyse the

potential sources of market power for hub airports. In section 3 we set up our basic model

(section 3.1), identify the strategic options for airlines and airports within the framework

(section 3.2) and derive possible market results (section 3.3). Based on these results, section

4 analyses dominant strategies and profit distribution games in order to find stable market

equilibrium. The characteristics of this equilibrium are used for giving recommendations on

airport regulation. Section 5 concludes.

2 SOURCES OF MARKET POWER FOR HUB AIRPORTS

Airports are multi-product companies offering services in the aviation- and non-aviation

market. It is generally agreed that non-aviation services of an airport such as lease of office

or retail space are subject to strong competition from high-street locations, so that high prices

for these services only reflect locational rents and no market power.3

In the aviation market, market power might occur due to the presence of monopolistic

bottlenecks (essential facilities). These are facilities which are essential to the provision of

airport services and which cannot be duplicated either because of cost reasons or because

of entry barriers. These conditions are generally fulfilled for airport infrastructure like

runways, taxiways or aprons.4 Whereas, concerning costs, there is only empirical evidence

for decreasing average costs of airport infrastructure up to 5 to 10m Work Load Units, 5 the

presence of high sunk costs, public opposition against airport projects, and long judicial

proceedings lead to high entry barriers for aviation services.6

With regard to hub airports, networks carriers often face lock-in effects at their hub airport.

This is mainly linked to asset specificity: From the airline perspective, there is specificity due

to the accumulation of traffic rights and slots at the airport,7 the matching of the flight

schedule on hub connections and idiosyncratic investments, for instance in maintenance

facilities. The costs of switching hub operations to another airport are high as investments,

which have been conducted at the present hub airport, have to be conducted at a new hub

3 See e.g. Malina (2006), p. 182, Forsyth (2004), de Wit (2004), pp. 85f.

4 See Kunz (1999), pp. 12f.

5 See Malina (2006), pp. 142ff.

6 See Forsyth (2006), pp. 350f and Starkie (2002), p. 65.

7 The latter is mainly important if grandfathering is the main mode of slot distribution.



3

airport again in order to ensure the functionality of the network.8 This lock-in effect might lead

to market power of hub airports in their business relationship to the airline, which the airport

might use in order to charge higher prices or offer lower service quality, so that the quasi-

rents of airline investment is (at least) partially transferred to the airport operator. However,

airports might be prevented from abusing market power due to idiosyncratic investment into

hub-specific airport infrastructure as well. In general, the airport operator depends on the

network carrier feeding flights into the airport, as the only option of generating the

throughput, which is needed for a sufficient utilization of airport infrastructure. This is due to

restrict bilateral agreements, which prevent carriers from other countries from operating 7th

freedom flights from the hub airport and possibly due to a lack of market knowledge and

market reach of those carriers. Moreover, the incentives of abusing market power in its

relationship to the hub carrier might further be reduced because of competition between

different airline-airport networks. By increasing airport charges or decreasing service quality,

a hub airport operator increases costs and decreases the service level and, therefore,

weakens the competitiveness of its hub carrier. This leads to lower demand for the hub

airline as passenger shift to other network airlines using other hubs and offering lower prices

or better services, which, in turn, leads to lower demand for services of the hub airport that

exploits market power.9

There is only scarce empirical evidence on market power of hub airports in the relationship to

the hub airline. Moreover, the degree of market power which is identified varies quite

substantially. Based on an analysis of ticket prices and journey time, Malina (2006) argues

that the two German hub airports Frankfurt and Munich face substantial competition for

transfer passengers from other European hubs such as Paris Charles de Gaulle,

Amsterdam, London Heathrow or Madrid which mitigates market power in relation to the hub

carrier.

Van Dender (2007) uses a data set of 55 US airports from 1998 to 2002 to analyze the

determinants of airport revenues and ticket prices. He applies a simultaneous equations

approach in order to account for different endogenous variables of demand, fare, delay, and

revenue. He finds that ticket prices are significantly higher at hub airport routes, which is

consistent to previous results by Borenstein, who finds that dominant positions of an airline at

an airport lead to higher prices.10 Van Dender shows that higher concentration of airlines at

an airport results in higher aeronautical revenues per passenger. However, he does not

provide evidence that hub airports charge significantly higher aeronautical charges than non-

hub airports, as the aeronautical revenues per departure are not influenced significantly by

the hub status.11

Research by Bel / Fageda (2010) focus on explaining airport charges for 100 European

airports in 2008 using a sample aircraft (Airbus A320) and a sample load factor of 70 % (105

passengers). They find that airport charges are higher, if the share of traffic of airline

alliances increases at a particular airport.

8 See Malina (2006), pp. 136ff or Fuhr / Beckers (2006), p. 394.

9 See Oum / Fu (2008), p. 13.

10 See Borenstein (1989).

11 See van Dender (2007), p. 327.



4

3 A MODEL OF HUB COMPETITION

In this section we develop a model of hub competition in order to analyze the incentives of

airports to exploit market power in relation to the hub airline. We first discuss the general

model framework and its assumptions (section 3.1). Afterwards, we identify the strategic

options for airlines and airports within this framework (section 3.2). In section 3.3 we find the

market equilibria.

3.1 Basic Model Set-up

The basic model comprises two market stages and two airline-airport systems as shown in

figure 1:

Figure 1 – Market Structure

Airline-Passenger market (downstream market)

On this airline-passenger-market we model the interaction between passengers and network

airlines. Passengers choose the relevant airline based on their preferences and airline

prices. Thus, in this market, prices are used as the profit optimizing parameter for airlines.

We limit the scope of this market to transfer passengers who use feeder flights into a hub

airport and continue their flight to their destination from the hub airport. Passengers who use

direct flights from or to the hub (hub O/D traffic) are not taken into account. The market

between airlines and passengers is modelled as an oligopolistic market, which is, given the

current airline market structure, a realistic assumption. The number of carriers and networks

is limited to two as a larger number would only add complexity without providing additional

value to the analysis.

Airport-Airline market (upstream market)

The market between airlines and airports is modelled as a monopolistic market. Hence, we

account for lock-in effects of the network carrier. Each airport only serves one network carrier

and the network carrier focuses its traffic to one hub airport which he cannot change.

Furthermore, we do not account for the possibility of countervailing power by the airlines. As

a consequence, if we find that a hub airport has no incentive to exploit market power in

relation to the hub carrier in this very rigid market framework, it will not do either in more

competitive market environments.



5

Based on the model framework, we define demand and cost functions. Let denote the

passenger demand directed to airline , the ticket price of airline and we define

the following demand function:

* +

In the analysis, we assume that the decline of demand due to a 1 € raise in ticket prices by

airline is higher than the additional demand for airline due to a 1 € raise in ticket price by

airline : As the model is symmetric, this implies, furthermore, that overall volumes in

the transfer passenger market grow as the level of ticket prices in this market decreases.

Parameter is the marginal passenger cost of the airport and the marginal passenger cost

of the airline (without airport fees). The airport fee per passenger at airport , the airport

which network carrier uses, is . Airport fixed costs are , airline fixed costs are . We

define the cost function of the airport and the cost function of the airline :

* +

( ) * +

Airlines and airports maximize profits . Their strategic parameters are airport fees (for

airports) and ticket prices (for airlines). We do not account for non-aviation revenues of the

airport. From a regulatory point of view we, therefore, model a worst-case scenario. If we find

that a hub airport operator has no or only limited incentives to exploit market power in the

relationship to the hub carrier without incorporating the effect of non-aviation revenues, it will

have even lower incentives, if non-aviation revenues are accounted for.

The airline networks are modelled as being heterogeneous for passengers. This is realistic,

as the networks differ in flight time and service quality. Thus, the market is a market with

heterogeneous products and Bertrand competition. The market equilibrium is described as a

Nash equilibrium. As the airlines’ costs are influenced by pricing decisions on the upstream

market, the market equilibrium is also determined by the charges which are set by the

airports. From the equilibrium on the downstream market we derive the demand functions for

the airports. The model is designed as a symmetric model without differences concerning

cost structures for airlines and airports as well as concerning demand structures.

3.2 Identification of Strategic Options for airlines and airports

Airlines and airports maximize their profits by setting prices on the upstream and

downstream market. However, they are also able to influence profits by the level of

cooperation between the market partners.

They either conduct profit maximization separately. In this strategy, the airport would exert a

profit maximizing strategy on its demand function, which is defined by the market equilibrium

on the downstream market. Thus, the airport tries to exploit market power to the maximal

extend which is possible in the given market framework. The equilibrium is determined by the

Nash equilibrium on the upstream market which affects the level of the equilibrium on the

oligopolistic airline-passenger downstream market.



6

Alternatively, the hub airline and its hub airport can also jointly optimize profits of the overall

network and distribute the profits to the partners afterwards. Thus, the structure of the market

is changed as airlines and airports use joint profit maximization within their network. Vertical

integration or hybrid forms of cooperation between airlines and airports might be used as a

contractual basis for joint profit maximization. Obviously, hub airports do not exploit market

power in this situation as they engage in joint profit maximization of the system.

In the following section 3.3 we analyze the market equilibria dependent on the different

strategies to design the business relationship between network carriers and their hubs

airports. We compare the market results to a reference scenario of perfect competition on the

upstream market. In this scenario, airports set their fee level at the level of marginal cost to

* +. Because we assume that airport fixed cost are high, this level of fees

results in long-term losses for the airports. Hence, we only use this market result as a

reference to evaluate the implications on market power and social welfare in different market

settings.

3.3 Market Results for different strategic options

Having identified the different strategic options for airlines and airports in the market

framework, we present the market results for different combinations of these strategic

options. At first, we present the reference scenario, in which airports choose a price level at

marginal costs. Afterwards, we develop the market results, if airports try to exploit market

power by separate profit maximization and compare it with the reference scenario. Last, we

derive the market equilibrium, if one or two networks conduct joint profit maximization within

their network.

3.3.1 Reference Scenario: Perfect Competition on the Upstream Market

In the downstream market between airlines and passengers, we model profit maximizing

airlines with given airport fees and profits:

* +

This yields the best response for airline on a given ticket price level of airline :

* +

By substituting the best response functions we find the Nash equilibrium in the downstream

market:

( )

(( ) )

* +



7

In the reference situation, we assume that there is perfect competition on the upstream

market between the network carrier and its hub airport. Thus, airports fix the level of charges

in the upstream market at marginal costs:

* +

Substitution into the Nash equilibrium function yields

( )

* +

As a consequence the level of passenger demand in the system is

( )

* +

This situation is hypothetical. It is only discussed in order to find a reference for the upstream

market, in which social welfare is maximized due to perfect competition on the upstream

market. This strategic option does not reflect rational behaviour in the given market

framework. Moreover, fees for the airport infrastructure at marginal costs are impossible in

our model framework in the long-run, as the airports would suffer long-term losses due to

high fixed costs, i.e. the cost of capital appropriation.

3.3.2 Separate profit maximisation

Compared to the reference situation, we do not change the structure of the downstream

market, which is presented in section 3.3.1. However, we substitute the downstream

equilibrium price into the downstream demand functions:

( ( )

* +

The result is the upstream demand function. It shows that the number of passengers, who

use airport , depends on the level of fees at airport as well as on the level of fees at airport

.12 Thus, although we account for lock-in effects of the airlines, hub airports do not hold a

monopoly position in this traffic segment, because high airport fees cause a disadvantage in

airline costs and thus, result in higher ticket prices in the respective network. Hence,

passengers change network or do not travel at all. As a consequence, market power of hub

airports is limited in this respect by downstream competition between network carriers.

We find the profit maximization condition of an airport as follows:

* +

From this condition we yield best responses for each airport to a given price level of the

airport of the antagonist system:

12

Demand at airport depends negatively on for and positively on for .



8

* +

By substituting the best response functions we find the Nash equilibrium in the upstream

market:

* +

Substituting this result into the downstream market equilibrium we find the overall equilibrium

in this market framework:

( )( ) * +

( )(( ) ( ) )

( )( ) * +

For our analysis we also calculate the profits of airlines, airports and the overall profits of the

system of airlines and airport. We calculate the following results:

( )( ) ( )

( )( ) * +

( ) ( )

( ) ( ) * +

( )( ) ( )

( ) ( ) ( ) * +

Although a downstream duopoly results in a lower level of market power for hub airports as

the airport’s demand function is not only dependent on the level of charges of the airport

itself but also of the level of charges of the airport in the antagonist system, we suppose that

there is at least some market power of hub airlines. Thus we analyse:

( )( ( ) ( ))

( )( )

For this conditions holds, if three additional conditions are true:

1. ( ( ) ( )) This condition implies that there is positive passenger

demand, if airlines and airports use marginal costs as prices. If this condition is not

true, nobody can serve the passengers without operational losses.

2.

. This condition holds if which implies that the decline of demand due to a

1 € raise in ticket prices by airline is higher than the additional demand for airline

due to a 1 € raise in ticket price by airline

3. ( ) which holds if √

for . This condition is true, if

for .



9

We can, therefore, conclude that in a market setting, in which airlines and airports conduct

independent profit maximization, ticket prices are higher compared to our reference situation

of perfect competition on the upstream market. Thus, independent profit maximization of

airlines and airports has negative impacts on social welfare which stem from lock-in effects of

network carriers at the hub airport.

3.3.3 System Optimization

Airlines and airports may also have an incentive to conduct joint profit maximization. Hence,

we also derive the market equilibrium, if this strategy is used. The cost function of the

network system equals the sum of the cost functions of airlines and airports reduced by the

revenues which the airports realize from their business relationship with the airline. The

systems’ revenues are gained in the market between passengers and the system. In our

model setting we obtain:

* +

We derive the condition for profit maximization of a system and find the best response of a

system to the pricing of a system :

* +

* +

System optimisation can either be done in both systems or in one system.

3.3.3.1 System Optimization of both systems

By substituting the best response functions we obtain the Nash equilibrium in this market:

* +

As a consequence the level of passenger demand in the system is found at

( )

* +

Joint profit maximization of hub airports and their network carrier replicates the market

results of perfect competition on the upstream market. Thus, this strategy is welfare

enhancing. If there is an incentive for airlines and airports to use this strategy, there is no

need for regulation of the business relationship between hub airlines and hub airports – at

least there is no need for regulation to achieve efficient market results that maximize social

welfare.

Furthermore, we calculate joint profits of the systems in this market equilibrium:



10

(( ) ( ) )

( ) * +

In this approach we only calculate the system profit as profits of airlines and airports cannot

be calculated without discussing the overall game of profit distribution between airlines and

airports. This is due to the fact that minimal profits of airlines and airports have to be

determined first, in order to decide whether profit sharing is possible that ensures

cooperation between airlines and airports. This will be determined in section 4 of this paper.

3.3.3.2 System Optimization in one system

We also consider whether there is an incentive for one network system to use joint profit

maximization while the other system does not. If this is not the case, system optimization

might be a good strategy in a one-shot game, but it does not evolve dynamically from vertical

separation between airlines and airports, which we find in most countries. Thus, we also

have to find the market equilibrium in this case. We assume that system 1 conducts joint

profit maximization whereas airports and airlines in system 2 optimize profits separately.

Therefore, system 1 optimizes profits assuming that there is a given ticket price of system 2.

We have already derived the reaction function for system 1:

Separate profit maximization of hub airports and network carriers in system 2 leads to the

following reaction function of airline 2 as derived in section 3.3.2:

Substitution of reaction functions yields the market equilibrium:

Thus, we obtain the demand function for airport 2:

(

Profit maximization of airport 2 yields:

( ) (( ) ) (( ) )

Thus, we calculate equilibrium ticket prices:



11

( ) (( ) ) (( ) )

( )( )

( ) (( ) ) ( )

( )( )

Comparing both prices, we find that if ( ( ) ( )) , and √

which is true for , . Thus, system optimization leads to lower prices compared to

the antagonist system which conducts separate optimization by airlines and airports. As a

consequence, there is considerable higher demand for system 1.

We calculate the following profits for this combination of strategic options:

( ) ( )

( ) ( ) ( )

( )( )

( ) ( ) ( )

Lower ticket prices in system 1 lead to additional passengers on the network, which, in turn,

lead to higher profits for system 1 in comparison to system 2, if, in addition to the above

mentioned conditions, . For , this condition is true. In

addition to these results, we also obtain profits of airlines and airports in system 2:

( )( )

( )( )

( )

( )

4 DOMINANT STRATEGIES, PROFIT DISTRIBUTION AND IMPLICATIONS FOR ECONOMIC REGULATION

In section 3 we have derived the market results for different combinations of strategic options

for airlines and airports. We have found that hub airports might not have an incentive to

exploit market power, if network airlines and their hub carriers conduct joint profit

maximization of their aviation system. However, we have not analyzed, so far, whether joint

profit maximization is a dominant strategy for the aviation systems. If it is dominant, it will

evolve as the equilibrium strategy in the market. In this case, there is no need for economic

regulation of the hub airline-hub airport relationship in order to ensure allocative efficiency as

the market result is welfare-enhancing with regard to the upstream market.

The structure of the game between the network systems is shown in figure 2:



12

Network 2

Netw

ork

1

Separate optimization Joint optimization

Separate Optimization

,

,

Joint Optimization ,

,

Figure 2 – Game Structure of Airline-Airport Networks

Because the model is symmetric, we know that

and

.

The ratios of the profits in different cases are as follows:

1.

. This condition holds as and . Furthermore, we have

to assume that is considerably higher than . This assumption is necessary, as it

ensures that there is enough additional traffic attracted by lower prices of both

systems in order to offset the profit decreasing effect of lower ticket prices. There is

empirical evidence that there is relevant growth of overall aviation markets as ticket

prices decrease,13 which implies that b is indeed considerably higher than d.

Furthermore, if ticket prices for the hub and spoke system decrease, some

passengers might also shift from O/D-connections to the hub and spoke network.

This would increase the difference between and even more.

2.

( ) ( )

( ) ( ) . This condition is true for

and ( ( ) ( )) , which implies that there is positive

passenger demand if airlines and airports use marginal costs as prices. Thus, if one

of the systems uses joint profit maximization and the other system does not, system

profits in the jointly optimized system are higher compared to a situation in which both

systems use joint profit maximization.

3. From condition 1 and 2 we conclude that

. As a consequence,

every system has an incentive to conduct joint profit maximization if the other system

does not.

4.

( ) ( )( )

( ) ( ) . This condition is true as long as

and . In a situation, in which the antagonist system uses joint profit

maximization, joint profit maximization is the best response to this strategy.

Based on these results, we determine the presence of dominant strategies. For network 1,

the best response to a separate optimization strategy by network 2 is joint optimization as

. Furthermore, if network 2 conducts joint optimization, we also find that

joint optimization is the best response by network 1 because

. Hence, joint

optimization is a dominant strategy or the best response to all strategies of system 2. As our

model is symmetric, the dominant strategy by network 2 is joint optimization as well. Thus,

network carriers and their hub airports have strong incentives to conduct joint profit

13

See for instance Intervistas (2007), pp. 43ff.



13

optimization in order to ensure the competitiveness of the overall network. This implication

arises although we account for lock-in effects of the network carrier at its hub airport.

The presence of a dominant strategy, in this case, implies that the joint profit maximization

equilibrium evolves dynamically even from a market with vertical separation. In this situation,

airlines and airports in one system face an incentive to use joint profit maximization

(condition 3). The best response of the antagonist is joint maximization as well (condition 4).

Best response to the other system is joint optimization again (condition 4 and symmetry).

Furthermore, there are no regrets in this equilibrium (condition 1). Thus, the equilibrium of

cooperation between network carriers and hub airlines in the market for transfer passengers

is stable. As a consequence, there is no need for regulators to intervene in the business

relationship between a network carrier and its hub airport in the market segment of transfer

passengers as joint profit maximization of airlines and airports ensures efficient and social

welfare optimal market results.

However, airlines and airports will only cooperate, if the strategy of joint profit maximization

maximizes individual profits of airlines and airports alike. We have already found that system

profits are higher if both systems use a joint profit maximization strategy.14 However, it is

necessary to find a suitable mechanism of profit sharing which ensures cooperation. In this

distributional game we can assume that airlines and airports will not conduct joint profit

maximization if the other partner in the network does not agree to use this strategy. Thus, we

have to study the profits that airlines and airports generate, as they do not use joint profit

maximization. We consider two situations:

In case that the antagonist system 1 uses joint profit maximization, airline 2 and airport

have the following optimal profits if they optimize separately:

( )

( )

( )( )

( )( ) . As shown above

(condition 4). Thus, a higher system profit can be

distributed to system 2, if the network carrier and the hub airport conduct joint profit

maximization. The minimum profit claim in order to enforce joint profit maximization is the

profit of the separation strategy, because both players are able to threaten the antagonist

with this situation. But as the system profit is higher, it is possible to solve this problem by

sharing additional profits. However, as set out above, it is necessary that there is

significant market growth of the hub and spoke network due to lower ticket prices in order

to ensure that this profit sharing mechanism exists.

In case that antagonist system 1 does not use joint profit maximization, the minimum

profit of airline 2 is

( )

( )

( ) ( ) and minimum profit of airport 2

is

( )( ) ( )

( )( ) . As shown above, we find that

(condition 3 and model symmetry). Thus, airlines and

airports are able to find a suitable profit sharing contract again.

14

The general conditions are shown above.



14

As a consequence, airlines and airports can find suitable profit sharing contracts which make

joint optimization profit enhancing for both partners. The minimum profits of the partners are

determined by the profits which they have in case of separate optimization which is the

plausible strategy in case that the antagonist tries to exploit the relevant player.

Our theoretical analysis, therefore, shows that there is no need to regulate the business

relationship between hub airports and hub airlines in the market for transfer passengers, as

competition between aviation networks, which use different hubs, limits incentives for hub

airports to exploit market power, which arises due to lock-in effects of the network carrier at

its hub airport. Moreover, regulators should encourage hub airports and their hub airlines to

negotiate long-term contracts of joint network optimization and profit sharing. One example of

such a contractual agreement can be found between Fraport, the operating company of

Frankfurt airport, and Lufthansa, who has bought a minority share (ca. 10 %) of Fraport. We

also find other forms of vertical cooperation like joint ventures between hub airports and

networks carriers (i.e. Terminal 2 at Munich Airport). These forms and other forms of

contractual agreements are important to network carriers and hub airports alike to ensure the

competitiveness of their common aviation network. These forms of cooperation do not

threaten, but rather advance market results. Economic regulation of this business

relationship is not necessary.

However, this policy implication is only valid for the market of transfer passengers as

discussed in this paper. In the O/D-segment, a hub airport should be able to skim additional

profits from the hub premium – even from the network carrier. Furthermore, access to the

airport, quality standards and a fair level of charges for other airlines need to be ensured.15

The latter is even more problematic in case of scarce capacity and the use of vertical

cooperation between hub airports and the respective network carrier. In this respect,

regulation is still necessary. Thus, there is strong evidence that asymmetric regulation is

reasonable at hub airports.

5 CONCLUSION

Competition on the downstream market for transfer passengers between network airlines is

an important element which affects the structure of the upstream market between hub

airports and the respective network carrier. Due to the fact that airline demand for hub airport

infrastructure is derived from the downstream passenger market, hub airports do not hold a

classical monopoly position in the upstream market. Even lock-in effects of hub airlines do

not change this notion. Based on a formal, theoretical model, we find evidence that network

carriers and hub airports have strong incentives to cooperate and use means of joint profit

maximization in the segment of transfer passengers. As the market results reflect results of

hypothetical perfect competition on the upstream market, there is no need for regulation of

the business relationship between network carriers and hub airports. Nevertheless, this does

not imply that hub airports should not be regulated at all, as market power of hub airport with

respect to O/D-traffic might exist and discriminatory behaviour of the airport is likely, if

15

See Serebrisky (2003), p. 2.



15

vertical cooperation between the network carrier and the hub airport is used. Thus, there is a

need for asymmetrical regulation of hub airports. On the one hand, regulators should support

long-term profit sharing contracts of network carriers and hub airports or other contractual

forms to ensure vertical cooperation. Thus, there are only weak incentives of market power

abuse by the airport. On the other hand, there is a need to ensure that the hub airport does

not discriminate against other airlines in the market segment of O/D passengers.

REFERENCES

Beckers, T. / J. P. Klatt / J. Kühling (2010): Entgeltregulierung der deutschen Flughäfen.

Reformbedarf aus ökonomischer und juristischer Sicht. Report prepared for the

German Airlines‘ Association.

Bel, G. / X. Fageda (2010): Privatization, Regulation and Airport Pricing: An Empirical

Analysis for Europe: In: Journal of Regulatory Economics, Vol. 37, pp. 142-161.

Borenstein, S. (1989): Hubs and High Fares: Dominance and Market Power in the U.S.

Airline Industry. In: RAND Journal of Economics, Vol. 20, pp. 344-365.

de Wit, J. (2004): Privatization and Regulation of Amsterdam Airport,. In: P. Forsyth et al.

(ed.): The Economic Regulation of Airports – Recent Developments in Australasia,

North America and Europe, pp.83-99.

Forsyth, P. (2004): Locational and monopoly rents at airports: creating them and shifting

them. In: Journal of Air Transport Management, Vol. 10, pp. 51-60.

Forsyth, P. (2006): Airport Comeptition: Regulatory Issues and Policy Implications. In: D.

Lee (ed.): Advances in Airline Economics, Vol. 1, pp. 347-368.

Fuhr, J. / T. Beckers (2006): Vertical Governance Between Airlines and Airports – A

Transaction Cost Analysis. In: Review of Network Economics, Vol. 5, pp. 386-412.

Intervistas (2007): Estimating Air Travel Demand Elasticities. Final Report prepared for the

IATA.

Kahn, A. E. (1993): The Competitive Consequences of Hub Dominance: A Case Study. In:

Review of Industrial Organization, Vol. 8, pp. 381-405.

Kunz, M. (1999): Airport Regulation: The Policy Framework. In: Phähler et al. (ed.): Airports

and Air Traffic: Regulation, Privatisation and Competition, pp. 9-55.

Lijesen, M.G. / P. Rietveld / P. Nijkamp (2000): Do European Carriers dominate their

Hubs? Tinbergen Institute Discussion Paper, TI 2000-071/3, Amsterdam.

Malina, R. (2006): Potenziale des Wettbewerbs und staatlicher Regulierungsbedarf von

Flughäfen in Deutschland. Göttingen.



16

Oum, T. / X. Fu (2008): Impacts of Airport on Airline Competition: Focus on Airport

Performance and Airport-Airline Vertical Relations. Discussion Paper No. 2008-17 of

the Joint Transport Research Center of OECD and International Transport Forum.

Serebrisky, T. (2003): Market Power: Airports: Vertical Integration between Airports and

Airlines. In: The World Bank Group: Public Policy for the Private Sector, Note No.

259.

Starkie, D. (2002): Airport Regulation and Competition. In: Journal of Air Transport

Management, Vol. 8, pp. 63-72.

van Dender, K. (2007): Determinants of Fares and Operating Revenues at US Airports. In:

Journal of Urban Economics, Vol. 62, pp.317-336.

diskussionspapier nr. 15 des instituts für ... · allroggen / malina: market power of hub airports...

Documents